Plant organellar RNA maturation.

Plant organellar RNA metabolism is run by a multitude of nucleus-encoded RNA-binding proteins (RBPs) that control RNA stability, processing, and degradation. In chloroplasts and mitochondria, these post-transcriptional processes are vital for the production of a small number of essential components of the photosynthetic and respiratory machinery-and consequently for organellar biogenesis and plant survival. Many organellar RBPs have been functionally assigned to individual steps in RNA maturation, often specific to selected transcripts. While the catalog of factors identified is ever-growing, our knowledge of how they achieve their functions mechanistically is far from complete. This review summarizes the current knowledge of plant organellar RNA metabolism taking an RBP-centric approach and focusing on mechanistic aspects of RBP functions and the kinetics of the processes they are involved in.

Insights into U-to-C RNA editing from the lycophyte Phylloglossum drummondii.

The lycophyte Phylloglossum drummondii is the sole inhabitant of its genus in the Huperzioideae group and one of a small minority of plants which perform uridine to cytidine RNA editing. We assembled the P. drummondii chloroplast and mitochondrial genomes and used RNA sequence data to build a comprehensive profile of organellar RNA editing events. In addition to many C-to-U editing events in both organelles, we found just four U-to-C editing events in the mitochondrial transcripts cob, nad1, nad5 and rpl2. These events are conserved in related lycophytes in the genera Huperzia and Phlegmariurus. De novo transcriptomes for three of these lycophytes were assembled to search for putative U-to-C RNA editing enzymes. Four putative U-to-C editing factors could be matched to the four mitochondrial U-to-C editing sites. Due to the unusually few numbers of U-to-C RNA editing sites, P. drummondii and related lycophytes are useful models for studying this poorly understood mechanism.

Mitochondrial atp1 mRNA knockdown by a custom-designed pentatricopeptide repeat protein alters ATP synthase.

Spontaneous mutations are rare in mitochondria and the lack of mitochondrial transformation methods has hindered genetic analyses. We show that a custom-designed RNA-binding pentatricopeptide repeat (PPR) protein binds and specifically induces cleavage of ATP synthase subunit1 (atp1) mRNA in mitochondria, significantly decreasing the abundance of the Atp1 protein and the assembled F1Fo ATP synthase in Arabidopsis (Arabidopsis thaliana). The transformed plants are characterized by delayed vegetative growth and reduced fertility. Five-fold depletion of Atp1 level was accompanied by a decrease in abundance of other ATP synthase subunits and lowered ATP synthesis rate of isolated mitochondria, but no change to mitochondrial electron transport chain complexes, adenylates, or energy charge in planta. Transcripts for amino acid transport and a variety of stress response processes were differentially expressed in lines containing the PPR protein, indicating changes to achieve cellular homeostasis when ATP synthase was highly depleted. Leaves of ATP synthase-depleted lines showed higher respiratory rates and elevated steady-state levels of numerous amino acids, most notably of the serine family. The results show the value of using custom-designed PPR proteins to influence the expression of specific mitochondrial transcripts to carry out reverse genetic studies on mitochondrial gene functions and the consequences of ATP synthase depletion on cellular functions in Arabidopsis.

Environmental Factors Influencing Stem Rot Development in Peanut: Predictors and Action Thresholds for Disease Management.

Peanuts grown in tropical, subtropical, and temperate regions are susceptible to stem rot, which is a soilborne disease caused by Athelia rolfsii. Due to the lack of reliable environmental-based scheduling recommendations, stem rot control relies heavily on fungicides that are applied at predetermined intervals. We conducted inoculated field experiments for six site-years in North Florida to examine the relationship between germination of A. rolfsii sclerotia: the inoculum, stem rot symptom development in the peanut crop, and environmental factors such as soil temperature (ST), soil moisture, relative humidity (RH), precipitation, evapotranspiration, and solar radiation. Window-pane analysis with hourly and daily environmental data for 5- to 28-day periods before each disease assessment were evaluated to select model predictors using correlation analysis, regularized regression, and exhaustive feature selection. Our results indicated that within-canopy ST (at 0.05 m belowground) and RH (at 0.15 m aboveground) were the most important environmental variables that influenced the progress of mycelial activity in susceptible peanut crops. Decision tree analysis resulted in an easy-to-interpret one-variable model (adjusted R2 = 0.51, Akaike information criterion [AIC] = 324, root average square error [RASE] = 14.21) or two-variable model (adjusted R2 = 0.61, AIC = 306, RASE = 10.95) that provided an action threshold for various disease scenarios based on number of hours of canopy RH above 90% and ST between 25 and 35°C in a 14-day window. Coupling an existing preseason risk index for stem rot, such as Peanut Rx, with the environmentally based predictors identified in this study would be a logical next step to optimize stem rot management. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Application of Hydrothermal Time Models to Predict Sclerotial Germination of Athelia rolfsii.

Athelia rolfsii, causal agent of "southern blight" disease, is a soilborne fungal pathogen with a wide host range of more than 500 species. This study's objectives were to (i) quantify the effects of two environmental factors, temperature and soil moisture, on germination of A. rolfsii inoculum (sclerotia), which is a critical event for the onset of disease epidemics and (ii) predict the timing of sclerotial germination by applying population-based threshold-type hydrothermal time (HTT) models. We conducted in vitro germination experiments with three isolates of A. rolfsii isolated from peanuts, which were tested at five temperatures (T), ranging from 17 to 40°C, four matric potentials (Ψm) between -0.12 and -1.57 MPa, and two soil types (fine sand and loamy fine sand), using a factorial design. When Ψm was maintained between -0.12 and -0.53 MPa, T from 22 to 34°C was found to be conducive to sclerotial germination (>50%). The HTT models were fitted for a range of T (22 to 34°C) and Ψm (-0.12 to -1.57 MPa) that accounted for 84% or more of variation in the timing of sclerotial germination. The estimated base T ranged between 0 and 4.5°C and the estimated base Ψm between -2.96 and -1.52 MPa. The results suggest that the HTT modeling approach is a suitable means of predicting the timing of A. rolfsii sclerotial germination. This HTT methodology can potentially be tested to fine-tune fungicide application timing and in-season A. rolfsii management strategies. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Sensor-Based Quantification of Peanut Disease Defoliation Using an Unmanned Aircraft System and Multispectral Imagery.

Early leaf spot (Passalora arachidicola) and late leaf spot (Nothopassalora personata) are two of the most economically important foliar fungal diseases of peanut, often requiring seven to eight fungicide applications to protect against defoliation and yield loss. Rust (Puccinia arachidis) may also cause significant defoliation depending on season and location. Sensor technologies are increasingly being utilized to objectively monitor plant disease epidemics for research and supporting integrated management decisions. This study aimed to develop an algorithm to quantify peanut disease defoliation using multispectral imagery captured by an unmanned aircraft system. The algorithm combined the Green Normalized Difference Vegetation Index and the Modified Soil-Adjusted Vegetation Index and included calibration to site-specific peak canopy growth. Beta regression was used to train a model for percent net defoliation with observed visual estimations of the variety 'GA-06G' (0 to 95%) as the target and imagery as the predictor (train: pseudo-R2 = 0.71, test k-fold cross-validation: R2 = 0.84 and RMSE = 4.0%). The model performed well on new data from two field trials not included in model training that compared 25 (R2 = 0.79, RMSE = 3.7%) and seven (R2 = 0.87, RMSE = 9.4%) fungicide programs. This objective method of assessing mid-to-late season disease severity can be used to assist growers with harvest decisions and researchers with reproducible assessment of field experiments. This model will be integrated into future work with proximal ground sensors for pathogen identification and early season disease detection.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Applications of Synthetic Pentatricopeptide Repeat Proteins.

RNA binding proteins play integral roles in the regulation of essential processes in cells, and as such are attractive targets for engineering to manipulate gene expression at the RNA level. Expression of transcripts in chloroplasts and mitochondria is heavily regulated by pentatricopeptide repeat (PPR) proteins. The diverse roles of PPR proteins, and their naturally modular architecture, makes them ideal candidates for engineering. Synthetic PPR proteins are showing great potential to become valuable tools for controlling the expression of plastid and mitochondrial transcripts. In this review, by 'synthetic' we mean both rationally modified natural PPR proteins and completely novel proteins designed using the principles learnt from their natural counterparts. We focus on the many different applications of synthetic PPR proteins, covering both their use in basic research to learn more about protein-RNA interactions, and their use to achieve specific outcomes in RNA processing and the control of gene expression. We describe the challenges associated with the design, construction and deployment of synthetic PPR proteins and provide perspectives on how they might be assembled and used in future biotechnology applications.

A unique C-terminal domain contributes to the molecular function of Restorer-of-fertility proteins in plant mitochondria.

Restorer-of-fertility (Rf) genes encode pentatricopeptide repeat (PPR) proteins that are targeted to mitochondria where they specifically bind to transcripts that induce cytoplasmic male sterility and repress their expression. In searching for a molecular signature unique to this class of proteins, we found that a majority of known Rf proteins have a distinct domain, which we called RfCTD (Restorer-of-fertility C-terminal domain), and its presence correlates with the ability to induce cleavage of the mitochondrial RNA target. A screen of 219 angiosperm genomes from 123 genera using a sequence profile that can quickly and accurately identify RfCTD sequences revealed considerable variation in RFL/RfCTD gene numbers across flowering plants. We observed that plant genera with bisexual flowers have significantly higher numbers of RFL genes compared to those with unisexual flowers, consistent with a role of these proteins in restoration of male fertility. We show that removing the RfCTD from the RFL protein RNA PROCESSING FACTOR 2-nad6 prevented cleavage of its RNA target, the nad6 transcript, in Arabidopsis thaliana mitochondria. We provide a simple way of identifying putative Rf candidates in genome sequences, new insights into the molecular mode of action of Rf proteins and the evolution of fertility restoration in flowering plants.

MSP1 encodes an essential RNA-binding pentatricopeptide repeat factor required for nad1 maturation and complex I biogenesis in Arabidopsis mitochondria.

Mitochondrial biogenesis relies on nuclearly encoded factors, which regulate the expression of the organellar-encoded genes. Pentatricopeptide repeat (PPR) proteins constitute a major gene family in angiosperms that are pivotal in many aspects of mitochondrial (mt)RNA metabolism (e.g. trimming, splicing, or stability). Here, we report the analysis of MITOCHONDRIA STABILITY/PROCESSING PPR FACTOR1 (MSP1, At4g20090), a canonical PPR protein that is necessary for mitochondrial functions and embryo development. Loss-of-function allele of MSP1 leads to seed abortion. Here, we employed an embryo-rescue method for the molecular characterization of msp1 mutants. Our analyses reveal that msp1 embryogenesis fails to proceed beyond the heart/torpedo stage as a consequence of a nad1 pre-RNA processing defect, resulting in the loss of respiratory complex I activity. Functional complementation confirmed that msp1 phenotypes result from a disruption of the MSP1 gene. In Arabidopsis, the maturation of nad1 involves the processing of three RNA fragments, nad1.1, nad1.2, and nad1.3. Based on biochemical analyses and mtRNA profiles of wild-type and msp1 plants, we concluded that MSP1 facilitates the generation of the 3' terminus of nad1.1 transcript, a prerequisite for nad1 exons a-b splicing. Our data substantiate the importance of mtRNA metabolism for the biogenesis of the respiratory system during early plant life.

Synthetic PPR proteins as tools for sequence-specific targeting of RNA.

In native systems, gene expression is regulated by RNA binding proteins. Such proteins have been the target of a great deal of recent research interest, due to the potential for harnessing these regulatory effects for the construction of new biotechnological tools. In particular, focus has been targeted on building synthetic RNA binding proteins for sequence-specific targeting of new RNA transcripts. Pentatricopeptide repeat (PPR) proteins make compelling candidates as synthetic RNA binding proteins to target and bind RNA transcripts of interest, due to their defined RNA binding "code", modular structure, and native capability to deliver catalytic C-terminal domains. In this review, we present a summary of up-to-date understanding of RNA site recognition by PPR proteins, progress towards the design of synthetic PPR proteins for RNA targeting in vitro and in vivo, highlight key areas for further research around these proteins and present an outlook for future applications for synthetic PPR proteins as biotechnological tools.

Alteration of Mitochondrial Transcript Expression in Arabidopsis thaliana Using a Custom-Made Library of Pentatricopeptide Repeat Proteins.

Pentatricopeptide repeat (PPR) proteins are considered a potential tool for manipulating organelle gene expression in plants because they can recognise a wide range of different RNA sequences, and the molecular basis for this sequence recognition is partially known and understood. A library of redesigned PPR proteins related to restorer-of-fertility proteins was created and transformed into plants in order to target mitochondrial transcripts. Ninety different variants tested in vivo showed a wide range of phenotypes. One of these lines, which displayed slow growth and downward curled leaves, showed a clear reduction in complex V. The phenotype was due to a specific cleavage of atp1 transcripts induced by a modified PPR protein from the library, validating the use of this library as a source of mitochondrial 'mutants'. This study is a step towards developing specific RNA targeting tools using PPR proteins that can be aimed at desired targets.

The GENOMES UNCOUPLED1 protein has an ancient, highly conserved role but not in retrograde signalling.

The pentatricopeptide repeat protein GENOMES UNCOUPLED1 (GUN1) is required for chloroplast-to-nucleus signalling when plastid translation becomes inhibited during chloroplast development in Arabidopsis thaliana, but its exact molecular function remains unknown. We analysed GUN1 sequences in land plants and streptophyte algae. We tested functional conservation by complementation of the Arabidopsis gun1 mutant with GUN1 genes from the streptophyte alga Coleochate orbicularis or the liverwort Marchantia polymorpha. We also analysed the transcriptomes of M. polymorpha gun1 knockout mutant lines during chloroplast development. GUN1 evolved within the streptophyte algal ancestors of land plants and is highly conserved among land plants but missing from the Rafflesiaceae that lack chloroplast genomes. GUN1 genes from C. orbicularis and M. polymorpha suppress the cold-sensitive phenotype of the Arabidopsis gun1 mutant and restore typical retrograde responses to treatments with inhibitors of plastid translation, even though M. polymorpha responds very differently to such treatments. Our findings suggest that GUN1 is an ancient protein that evolved within the streptophyte algal ancestors of land plants before the first plants colonized land more than 470 million years ago. Its primary role is likely to be in chloroplast gene expression and its role in chloroplast retrograde signalling probably evolved more recently.

Effects of Grass-Based Crop Rotation, Nematicide, and Irrigation on the Nematode Community in Cotton.

Plant-parasitic and free-living nematodes - bacterivores, fungivores, omnivores, predators - comprise the nematode community. Nematicide application and crop rotation are important tools to manage plant-parasitic nematodes, but effects on free-living nematodes and nematode ecological indices need further study. The nematicide fluopyram was recently introduced in cotton (Gossypium hirsutum) production and its effects on the nematode community need assessment. This research was conducted in 2017 and 2018 at a long-term field site in Quincy, FL where perennial grass/sod-based (bahiagrass, Paspalum notatum) and conventional cotton rotations were established in 2000. The objective of this research was to evaluate the effects of fluopyram nematicide, crop rotation phase, and irrigation on free-living nematodes and nematode ecological indices based on three soil sampling dates each season. We did not observe consistent effects of crop rotation phase on free-living nematodes or nematode ecological indices. Only omnivores were consistently negatively impacted by fluopyram. Nematode ecological indices reflected this negative effect by exhibiting a degraded/ stressed environmental condition relative to untreated plots. Free-living nematodes were not negatively impacted by nematicide when sod-based rotation was used.

Plant organellar RNA editing: what 30 years of research has revealed.

The central dogma in biology defines the flow of genetic information from DNA to RNA to protein. Accordingly, RNA molecules generally accurately follow the sequences of the genes from which they are transcribed. This rule is transgressed by RNA editing, which creates RNA products that differ from their DNA templates. Analyses of the RNA landscapes of terrestrial plants have indicated that RNA editing (in the form of C-U base transitions) is highly prevalent within organelles (that is, mitochondria and chloroplasts). Numerous C→U conversions (and in some plants also U→C) alter the coding sequences of many of the organellar transcripts and can also produce translatable mRNAs by creating AUG start sites or eliminating premature stop codons, or affect the RNA structure, influence splicing and alter the stability of RNAs. RNA-binding proteins are at the heart of post-transcriptional RNA expression. The C-to-U RNA editing process in plant mitochondria involves numerous nuclear-encoded factors, many of which have been identified as pentatricopeptide repeat (PPR) proteins that target editing sites in a sequence-specific manner. In this review we report on major discoveries on RNA editing in plant organelles, since it was first documented 30 years ago.

Predictive Modeling of Brown Rust of Sugarcane Based on Temperature and Relative Humidity in Florida.

Logistic regression models were developed from 5 years (2014 to 2018) of disease severity and weather data in an attempt to predict brown rust of sugarcane at the Everglades Research and Education Center in Belle Glade, Florida. Disease severity (percentage area of the top visible dewlap leaf covered by rust) was visually assessed in the field every 2 weeks for two varieties susceptible to brown rust. A total of 250 variables were derived from weather data for 10- to 40-day periods before each brown rust assessment day. A subset of these variables were then evaluated as potential predictors of severity of brown rust based on their individual correlation or their biological meaningfulness. Analyses of correlation and stepwise logistic regression allowed us to identify afternoon humid thermal ratio (AHTR), temperature-based duration variables, and their interaction terms as the most significant variables associated with brown rust epidemics of sugarcane in Florida. The nine best predictive models were identified based on model accuracy, sensitivity, specificity, and estimates of the prediction error. The prediction accuracy of these models ranged from 73 to 85%. Single-variable model BR2 (based on AHTR) classified 89% of the epidemic and 81% of the nonepidemic status of the disease. More than 83% of the epidemics and 81% of the nonepidemic status of sugarcane brown rust was correctly classified via multiple-variable models. These models can be used as components of a rust disease warning system to assist in the management of brown rust epidemics of sugarcane in south Florida.

Peanut disease epidemiology under dynamic microclimate conditions and management practices in North Florida.

Diverse field characteristics, weather patterns, and management practices can result in variable microclimates. The objective was to relate in-field microclimate conditions with peanut diseases and yield and determine the effect of irrigation and fungicides within these environments. Irrigation did not have a major impact on disease and yield. Stem rot (Athelia rolfsii) and early (Passalora arachidicola) and late (Nothopassalora personata) leaf spot were most affected by changes in environmental patterns across seasons. Average non-treated stem rot was 12.9% in 2017 which dropped considerably in 2018 to 0.2% but emerged again in 2019 to 3.2%. Stem rot incidence varied across the field, and the response to fungicides depended on management zone. Leaf spot defoliation in non-treated plots was severe in 2019 reaching an average of 73% at 126 days after planting but only reached 15% in 2017 and 35% in 2019 at the same stage. A low-input fungicide schedule was able to reduce foliar disease in all zones and seasons, but the microclimatic conditions in the low-lying area favored leaf spot in 2017 and 2018 although not in the dryer 2019 season. Seasonal differences in disease and plant growth affected the level of protection against average yield loss using a standard low-input program which in 2017 (527 kg/ha) was not as great as 2018 (2,235 kg/ha) or 2019 (1,763 kg/ha). Disease prediction models built on dynamic environmental factors in the context of multiple pathogens and natural field conditions could be developed to improve within-season management decisions for more efficient fungicide inputs.

The coordinated action of PPR4 and EMB2654 on each intron half mediates trans-splicing of rps12 transcripts in plant chloroplasts.

The pentatricopeptide repeat proteins PPR4 and EMB2654 have been shown to be required for the trans-splicing of plastid rps12 transcripts in Zea mays (maize) and Arabidopsis, respectively, but their roles in this process are not well understood. We investigated the functions of the Arabidopsis and Oryza sativa (rice) orthologs of PPR4, designated AtPPR4 (At5g04810) and OsPPR4 (Os4g58780). Arabidopsis atppr4 and rice osppr4 mutants are embryo-lethal and seedling-lethal 3 weeks after germination, respectively, showing that PPR4 is essential in the development of both dicot and monocot plants. Artificial microRNA-mediated mutants of AtPPR4 displayed a specific defect in rps12 trans-splicing, with pale-green, yellowish or albino phenotypes, according to the degree of knock-down of AtPPR4 expression. Comparison of RNA footprints in atppr4 and emb2654 mutants showed a similar concordant loss of extensive footprints at the 3' end of intron 1a and at the 5' end of intron 1b in both cases. EMB2654 is known to bind within the footprint region in intron 1a and we show that AtPPR4 binds to the footprint region in intron 1b, via its PPR motifs. Binding of both PPR4 and EMB2654 is essential to juxtapose the two intron halves and to maintain the RNAs in a splicing-competent structure for the efficient trans-splicing of rps12 intron 1, which is crucial for chloroplast biogenesis and plant development. The similarity of EMB2654 and PPR4 orthologs and their respective binding sites across land plant phylogeny indicates that their coordinate function in rps12 trans-splicing has probably been conserved for 500 million years.

High intraspecific diversity of Restorer-of-fertility-like genes in barley.

Nuclear restorer of fertility (Rf) genes suppress the effects of mitochondrial genes causing cytoplasmic male sterility (CMS), a condition in which plants fail to produce viable pollen. Rf genes, many of which encode RNA-binding pentatricopeptide repeat (PPR) proteins, are applied in hybrid breeding to overcome CMS used to block self-pollination of the seed parent. Here, we characterise the repertoire of restorer-of-fertility-like (RFL) PPR genes in barley (Hordeum vulgare). We found 26 RFL genes in the reference genome ('Morex') and an additional 51 putative orthogroups (POGs) in a re-sequencing data set from 262 barley genotypes and landraces. Whereas the sequences of some POGs are highly conserved across hundreds of barley accessions, the sequences of others are much more variable. High sequence variation strongly correlates with genomic location - the most variable genes are found in a cluster on chromosome 1H. A much higher likelihood of diversifying selection was found for genes within this cluster than for genes present as singlets. This work includes a comprehensive analysis of the patterns of intraspecific variation of RFL genes. The RFL sequences characterised in this study will be useful for the development of new markers for fertility restoration loci.

Towards a plant model for enigmatic U-to-C RNA editing: the organelle genomes, transcriptomes, editomes and candidate RNA editing factors in the hornwort Anthoceros agrestis.

Hornworts are crucial to understand the phylogeny of early land plants. The emergence of 'reverse' U-to-C RNA editing accompanying the widespread C-to-U RNA editing in plant chloroplasts and mitochondria may be a molecular synapomorphy of a hornwort-tracheophyte clade. C-to-U RNA editing is well understood after identification of many editing factors in models like Arabidopsis thaliana and Physcomitrella patens, but there is no plant model yet to investigate U-to-C RNA editing. The hornwort Anthoceros agrestis is now emerging as such a model system. We report on the assembly and analyses of the A. agrestis chloroplast and mitochondrial genomes, their transcriptomes and editomes, and a large nuclear gene family encoding pentatricopeptide repeat (PPR) proteins likely acting as RNA editing factors. Both organelles in A. agrestis feature high amounts of RNA editing, with altogether > 1100 sites of C-to-U and 1300 sites of U-to-C editing. The nuclear genome reveals > 1400 genes for PPR proteins with variable carboxyterminal DYW domains. We observe significant variants of the 'classic' DYW domain, in the meantime confirmed as the cytidine deaminase for C-to-U editing, and discuss the first attractive candidates for reverse editing factors given their excellent matches to U-to-C editing targets according to the PPR-RNA binding code.

Weather-Based Predictive Modeling of Orange Rust of Sugarcane in Florida.

Epidemics of sugarcane orange rust (caused by Puccinia kuehnii) in Florida are largely influenced by prevailing weather conditions. In this study, we attempted to model the relationship between weather conditions and rust epidemics as a first step toward development of a decision aid for disease management. For this purpose, rust severity data were collected from 2014 through 2016 at the Everglades Research and Education Center, Belle Glade, Florida, by recording percentage of rust-affected area of the top visible dewlap leaf every 2 weeks from three orange rust susceptible cultivars. Hourly weather data for 10- to 40-day periods prior to each orange rust assessment were evaluated as potential predictors of rust severity under field conditions. Correlation and stepwise regression analyses resulted in the identification of nighttime (8 PM to 8 AM) accumulation of hours with average temperature 20 to 22°C as a key predictor explaining orange rust severity. The five best regression models for a 30-day period prior to disease assessment explained 65.3 to 76.2% of variation of orange rust severity. Prediction accuracy of these models was tested using a case control approach with disease observations collected in 2017 and 2018. Based on receiver operator characteristic curve analysis of these two seasons of test data, a single-variable model with the nighttime temperature predictor mentioned above gave the highest prediction accuracy of disease severity. These models have potential for use in quantitative risk assessment of sugarcane rust epidemics.